{"id":"https://openalex.org/W4413074451","doi":"https://doi.org/10.1109/ssp64130.2025.11073307","title":"Towards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional Network","display_name":"Towards Lightweight Hyperspectral Image Super-Resolution with Depthwise Separable Dilated Convolutional Network","publication_year":2025,"publication_date":"2025-06-08","ids":{"openalex":"https://openalex.org/W4413074451","doi":"https://doi.org/10.1109/ssp64130.2025.11073307"},"language":"en","primary_location":{"id":"doi:10.1109/ssp64130.2025.11073307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp64130.2025.11073307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100645878","display_name":"Usman Muhammad","orcid":"https://orcid.org/0000-0001-7191-0245"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Usman Muhammad","raw_affiliation_strings":["Aalto University,Department of Computer Science,Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalto University,Department of Computer Science,Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036133390","display_name":"Jorma Laaksonen","orcid":"https://orcid.org/0000-0001-7218-3131"},"institutions":[{"id":"https://openalex.org/I9927081","display_name":"Aalto University","ror":"https://ror.org/020hwjq30","country_code":"FI","type":"education","lineage":["https://openalex.org/I9927081"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Jorma Laaksonen","raw_affiliation_strings":["Aalto University,Department of Computer Science,Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aalto University,Department of Computer Science,Finland","institution_ids":["https://openalex.org/I9927081"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5006505402","display_name":"Lyudmila Mihaylova","orcid":"https://orcid.org/0000-0001-5856-2223"},"institutions":[{"id":"https://openalex.org/I91136226","display_name":"University of Sheffield","ror":"https://ror.org/05krs5044","country_code":"GB","type":"education","lineage":["https://openalex.org/I91136226"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lyudmila Mihaylova","raw_affiliation_strings":["University of Sheffield,School of Electrical and Electronic Engineering,United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Sheffield,School of Electrical and Electronic Engineering,United Kingdom","institution_ids":["https://openalex.org/I91136226"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"91","last_page":"95"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11105","display_name":"Advanced Image Processing Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10688","display_name":"Image and Signal Denoising Methods","score":0.9998000264167786,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hyperspectral-imaging","display_name":"Hyperspectral imaging","score":0.8828389644622803},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7318217754364014},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6238478422164917},{"id":"https://openalex.org/keywords/separable-space","display_name":"Separable space","score":0.5656077861785889},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.486723929643631},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.48629030585289},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4681808054447174},{"id":"https://openalex.org/keywords/resolution","display_name":"Resolution (logic)","score":0.4440538287162781},{"id":"https://openalex.org/keywords/image-resolution","display_name":"Image resolution","score":0.4332151412963867},{"id":"https://openalex.org/keywords/superresolution","display_name":"Superresolution","score":0.42165833711624146},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.33597075939178467},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.14057913422584534}],"concepts":[{"id":"https://openalex.org/C159078339","wikidata":"https://www.wikidata.org/wiki/Q959005","display_name":"Hyperspectral imaging","level":2,"score":0.8828389644622803},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7318217754364014},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6238478422164917},{"id":"https://openalex.org/C70710897","wikidata":"https://www.wikidata.org/wiki/Q680081","display_name":"Separable space","level":2,"score":0.5656077861785889},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.486723929643631},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.48629030585289},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4681808054447174},{"id":"https://openalex.org/C138268822","wikidata":"https://www.wikidata.org/wiki/Q1051925","display_name":"Resolution (logic)","level":2,"score":0.4440538287162781},{"id":"https://openalex.org/C205372480","wikidata":"https://www.wikidata.org/wiki/Q210521","display_name":"Image resolution","level":2,"score":0.4332151412963867},{"id":"https://openalex.org/C141239990","wikidata":"https://www.wikidata.org/wiki/Q957423","display_name":"Superresolution","level":3,"score":0.42165833711624146},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33597075939178467},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.14057913422584534},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ssp64130.2025.11073307","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ssp64130.2025.11073307","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE Statistical Signal Processing Workshop (SSP)","raw_type":"proceedings-article"},{"id":"pmh:oai:eprints.whiterose.ac.uk:226158","is_oa":false,"landing_page_url":"https://orcid.org/0000-0001-5856-2223>","pdf_url":null,"source":{"id":"https://openalex.org/S4306400854","display_name":"White Rose Research Online (University of Leeds, The University of Sheffield, University of York)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I2800616092","host_organization_name":"White Rose University Consortium","host_organization_lineage":["https://openalex.org/I2800616092"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":null,"raw_type":"Proceedings Paper"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":39,"referenced_works":["https://openalex.org/W2011315899","https://openalex.org/W2214802144","https://openalex.org/W2242218935","https://openalex.org/W2503339013","https://openalex.org/W2889043082","https://openalex.org/W2902459419","https://openalex.org/W2903595434","https://openalex.org/W2909332219","https://openalex.org/W2946893679","https://openalex.org/W2963163009","https://openalex.org/W2963372104","https://openalex.org/W2963442801","https://openalex.org/W2963645458","https://openalex.org/W2963840672","https://openalex.org/W2971595222","https://openalex.org/W3002092414","https://openalex.org/W3027120144","https://openalex.org/W3027528898","https://openalex.org/W3047895866","https://openalex.org/W3096641820","https://openalex.org/W3107716502","https://openalex.org/W3124196789","https://openalex.org/W3202459663","https://openalex.org/W3208181816","https://openalex.org/W4205841215","https://openalex.org/W4281855345","https://openalex.org/W4297775537","https://openalex.org/W4309839525","https://openalex.org/W4386590665","https://openalex.org/W4386766980","https://openalex.org/W4391133199","https://openalex.org/W4391137563","https://openalex.org/W4392271070","https://openalex.org/W4393156377","https://openalex.org/W4399666343","https://openalex.org/W4400914090","https://openalex.org/W4402262625","https://openalex.org/W6696085341","https://openalex.org/W6737664043"],"related_works":["https://openalex.org/W2072166414","https://openalex.org/W3209970181","https://openalex.org/W2317401237","https://openalex.org/W1990800631","https://openalex.org/W2167120702","https://openalex.org/W2579567122","https://openalex.org/W4389989350","https://openalex.org/W3004000015","https://openalex.org/W4288598071","https://openalex.org/W2559771220"],"abstract_inverted_index":{"Deep":[0],"neural":[1],"networks":[2],"have":[3],"demonstrated":[4],"highly":[5],"competitive":[6,172],"performance":[7,173],"in":[8,76],"super-resolution":[9,26,186],"(SR)":[10],"for":[11,125,183],"natural":[12],"images":[13],"by":[14,80],"learning":[15],"mappings":[16],"from":[17],"low-resolution":[18],"(LR)":[19],"to":[20,32,94,107,119],"high-resolution":[21],"(HR)":[22],"images.":[23],"However,":[24],"hyperspectral":[25,178,184],"remains":[27],"an":[28,148],"ill-posed":[29],"problem":[30],"due":[31],"the":[33,38,41,63,81,108,121,126,159],"high":[34,57],"spectral":[35,132,155,163],"dimensionality":[36],"of":[37,43,59,71,128,161],"data":[39],"and":[40,111,131,153,164],"scarcity":[42],"available":[44,177,193],"training":[45],"samples.":[46],"Moreover,":[47],"existing":[48],"methods":[49],"often":[50,74],"rely":[51],"on":[52,174],"large":[53],"models":[54],"with":[55,65],"a":[56,86,114,138,154],"number":[58],"parameters":[60],"or":[61,67],"require":[62],"fusion":[64,117],"panchromatic":[66],"RGB":[68],"images,":[69],"both":[70,129,162],"which":[72],"are":[73,191],"impractical":[75],"real-world":[77],"scenarios.":[78],"Inspired":[79],"MobileNet":[82,109],"architecture,":[83,110],"we":[84,136],"introduce":[85],"lightweight":[87],"depthwise":[88,103],"separable":[89,104],"dilated":[90,115],"convolutional":[91],"network":[92],"(DSDCN)":[93],"address":[95],"aforementioned":[96],"challenges.":[97],"Specifically,":[98],"our":[99],"model":[100,122,169],"leverages":[101],"multiple":[102],"convolutions,":[105],"similar":[106],"further":[112],"incorporates":[113],"convolution":[116],"block":[118],"make":[120],"more":[123],"flexible":[124],"extraction":[127],"spatial":[130,165],"features.":[133],"In":[134],"addition,":[135],"propose":[137],"custom":[139],"loss":[140],"function":[141],"that":[142],"combines":[143],"mean":[144],"squared":[145],"error":[146],"(MSE),":[147],"L2":[149],"norm":[150],"regularization-based":[151],"constraint,":[152],"angle-based":[156],"loss,":[157],"ensuring":[158],"preservation":[160],"details.":[166],"The":[167,188],"proposed":[168],"achieves":[170],"very":[171],"two":[175],"publicly":[176,192],"datasets,":[179],"making":[180],"it":[181],"well-suited":[182],"image":[185],"tasks.":[187],"source":[189],"codes":[190],"at:":[194],"https://github.com/Usman1021/lightweight.":[195]},"counts_by_year":[{"year":2025,"cited_by_count":5}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
